Company Description

Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their life easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere.

More about our mission.

Job Description

The team you will join: Fraud Decisioning team

The team is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team is responsible for developing and enhancing payment fraud detection systems. Software engineers, data analysts, and data scientists collaborate on a daily basis to continuously improve our systems and provide support to our fraud investigation team.

Our vision is:

Build a globally scalable payment fraud prevention and detection real-time engine to keep Wise as a secure environment for our legitimate customers.Utilise machine learning techniques to identify potential risks associated with customer activity.Foster a strong partnership between our fraud investigators and the product team to develop solutions that leverage the expertise of fraud prevention specialists.Not only meet the requirements set by regulators and auditors but also surpass their expectations.

What does it take?  

Demonstrated experience delivering at least 3 full-lifecycle Java/JVM-based projects, each spanning 3-6 months in durationExperience with CI/CD pipelines and Distributed and Concurrent SystemsHands-on experience with Kafka, Kafka Streams or Apache FlinkExperience with OLAP databases or data-lakes with Kafka ingestion is a plusA strong product mindset and passion for user experience, you prioritise work with the customers in mind and make data-driven decisions to fix customer pain-pointsYou believe in and follow best coding practices, code reviews and open feedbackBeing able to work autonomously on customer problems is a key to success - you take responsibility and end-to-end ownership of your projects: drive and own them to make sure we hit the goals we want to achieveClose collaboration with product managers, data scientists, data analysts, engineers and other product teams is a must have and is something to expect to happen on a daily basis.Great communication skills (both verbal and written) and the ability to articulate complex, technical concepts to non-technical audienceHands-on experience working with relational and non-relational databases, query optimisations, designing and evolving schemasExperience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plusBeing able to propose technical solutions that optimise for latency and throughput at the same time - aka: p99 end-to-end latency is under 1 second for real-time payment fraud checks even when a significant amount of transactions are in the system.

What does success look like?

You'll be having a real world impact by building financial crime prevention systems which protect customers from falling victims of fraud or scamsYou’ll have onboarded and found your place through understanding your team and tribe vision and how you can contributeYou’ll understand how our values can help you guide your workYou’ll understand the reasons behind problematic payments and customer difficulties and how to go about solving themYou’ll be raising the automation level to enable scaling of the productUnderstand our customers and the impact our product makes in their lives You’ll help us scale-up and build a world class money transfer product by finding solutions to our technical challenges and opportunities
Additional Information

For everyone, everywhere. We're people building money without borders  — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.